Priority action queue
Synthesising command picture
State threat board
| District | 30d | Trend | Clear% | Level |
|---|
Proactive deployment forecast
Official Crime Review
Published totals · National Crime Records Bureau & Karnataka State Police · real, citable figures
Bengaluru City — crimes by head (2023)
| Crime head | Cases 2023 | Source |
|---|
Karnataka State (2023)
12-month crime trend
Case lifecycle
Pipeline from registered FIR → court → disposal. Resolution = solved + closed as a share of all cases.
Crime type composition
Clearance rate by district
Incident map · all districts
Active hotspot
Normal district
click any dot for detail · drag the slider to play months
About locations: the illustrative sample cases are placed approximately (area-level, not the true spot — record-level locations are confidential). FIRs registered in this console are pinned at the exact spot the officer marks on the form's map.
District workload
| District | Cases | Open | Clear% |
|---|
Police station performance
| Station | Total | Open | Cleared | Clearance |
|---|
City Commissionerates
Police Ranges
Repeat-offender watchlist
| # | Offender | Role | Primary MO | Cases | Last active | Risk priority |
|---|
Risk = investigation priority, not a prediction. Score (0–100) is itemised from qualifying case count, recency, repeated vehicle-borne MO, and links to known associates. An officer decides — the system only ranks and shows its working.
Link analysis
Hub
Key connector
Ring member
Co-accused
Associate
Network read-out
Mapping links
How to read this: each dot is a person; lines join people accused together or known to associate. The hub is the most-connected offender; a key connector holds two sub-groups together — removing one splits the network apart. Hover any dot to isolate its links. Built only from real case records — nothing inferred.
Computing MO fingerprints
Incidents by weekday
Seasonal & event lens
Recent case register
| Case No. | Type | Date | Station | Status |
|---|
Register a new FIR
Local police file the case here. It is validated server-side (recognised crime types & districts, no future dates, FIR-number format) and immediately joins the live analytics — one source of truth, no separate data entry. Write access is limited to Station Officer, Investigator and Supervisor roles; every registration is audited.
Import case data
The real-world intake path. Every FIR in Karnataka is already digital (CCTNS); SCRB can export it as a spreadsheet. Upload that export here — every row passes the same validation rulebook as a hand-registered FIR (recognised types & districts, station names normalised, no future dates, no duplicates), you review the result, then confirm the write. Rejected rows are listed with the reason and line number — fix and re-upload just those. Access: District Command (own district only) and SCRB Analyst (statewide). Every import is audited.
Social context · —
Why crime clusters here — drivers
How criminologists read this
Who is involved
Who is being targeted — community impact
Authorised feed connectors
Corroboration ladders
The evidence ladder
What this prevents
Money-flow trail
Money-flow traces
Priority — investigate these accounts first
Laundering rings
Traced cash-out by ring
Deposits by betting app
Telegram recruitment
Betting-app account rotation
| Betting merchant | Mule accounts used | Deposits | Txns |
|---|
Illustrative sample · the same engine runs on real bank STR / UPI feeds. Accounts pseudonymised · leads, not verdicts.
Ask — English or ಕನ್ನಡ
Type, or tap the mic to speak
Evidence · grounded records
Every number here is worked out live from the real case database — nothing is estimated or made up.